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http://dx.doi.org/10.14481/jkges.2017.18.12.47

Analysis of Hazard Areas by Sediment Disaster Prediction Techniques Based on Ground Characteristics  

Choi, Wonil (Gyeonggi Disaster Management Institute)
Choi, Eunhwa (Gyeonggi Disaster Management Institute)
Baek, Seungcheol (Department of Civil Engineering, Andong National University)
Publication Information
Journal of the Korean GEO-environmental Society / v.18, no.12, 2017 , pp. 47-57 More about this Journal
Abstract
In this study, a predictive analysis was conducted on sediment disaster hazard area by selecting six research areas (Chuncheon, Seongnam, Sejong, Daejeon, Miryang and Busan) among the urban sediment disaster preliminary focus management area. The models that were used in the analysis were the existing models (SINMAP and TRIGRS) that are commonly used in predicting sediment disasters as well as the program developed through this study (LSMAP). A comparative analysis was carried out on the results as a means to review the applicability of the developed model. The parameters used in the predictions of sediment disaster hazard area were largely classified into topographic, soil, forest physiognomy and rainfall characteristics. A predictive analysis was carried out using each of the models, and it was found that the analysis using SINMAP, compared to LSMAP and TRIGRS, resulted in a prediction of a wider hazard zone. These results are considered to be due to the difference in analysis parameters applied to each model. In addition, a comparison between LSMAP, where the forest physiognomy characteristics were taken into account, and TRIGRS showed that similar tendencies were observed within a range of -0.04~2.72% for the predicted hazard area. This suggests that the forest physiognomy characteristics of mountain areas have diverse impacts on the stability of slopes, and serve as an important parameter in predicting sediment disaster hazard area.
Keywords
Sediment disaster; Prediction of hazard areas; LSMAP; SINMAP; TRIGRS;
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Times Cited By KSCI : 7  (Citation Analysis)
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